Fair and Efficient Electric Vehicle Charging Scheduling Optimization Considering the Maximum Individual Waiting Time and Operating Cost

Abstract

The shortage of charging piles and the soaring power demand of charging stations will lead to long waiting times for electric vehicles (EVs) that need to accomplish charging tasks. Most charging scheduling methods pay more attention to the overall waiting time, and they usually do not consider the time-aware fairness among EV users. Moreover, it has become important to schedule EVs effectively to minimize the operating cost of the station. This paper considers the trade-off between the time-aware fairness and overall waiting time of EVs to optimize the individual waiting time. A novel metric, the time-aware fairness index (TAFI), is proposed to evaluate the fairness performance for competing EVs. Therefore, a bi-objective charging and discharging scheduling problem is formulated. A novel online scheduling algorithm based on the dynamic schedulable time of EVs and the energy demand fluctuation of the station is proposed to obtain an optimal scheduling solution. Experimental results indicate that our method effectively reduces the total waiting time while minimizing the maximum individual waiting time and reducing the operating cost of the station. Moveover, the TAFI results confirm that the desired fairness behavior occurs.